PROJECT / 01
MACHINE LEARNING · DATA PRODUCT
Procurement Intelligence
A spend and price intelligence platform built on 5.7M+ public procurement transactions.
DATA SCIENCE · AI ENGINEERING
Matheus Mori
Data Scientist
& AI Engineer
Building production-oriented AI, machine learning and data products.
I work across data, machine learning and AI — turning complex problems into systems people can actually use.
↓ Scroll01 / ABOUT
I build at the intersection of
data, machine learning and AI.
BACKGROUND
- Statistics
- Data Science
- Machine Learning
- Analytics
CURRENT DIRECTION
- AI Engineering
- Applied AI
- Production ML
I'm a statistician and data professional focused on turning analytical problems into reliable products and systems.
My background spans analytics, machine learning, experimentation and decision-support products. Today, I'm increasingly focused on AI engineering — especially systems that combine LLMs, retrieval, agents, evaluation, APIs and production-oriented software practices.
DATA SCIENCE
Statistical modeling, experimentation, forecasting and machine learning.
AI ENGINEERING
LLM applications, RAG, agents, evaluation and AI systems.
DATA PRODUCTS
Turning models and analysis into tools people can actually use.
02 / SELECTED WORK
Systems designed to
solve real problems.
A selection of machine learning systems, AI workflows and data products.
PROJECT / 02
AI AUTOMATION · PRODUCTIVITY SYSTEM
Application Job
An AI-assisted workflow that turns job descriptions and verified career evidence into tailored applications.
PROJECT / 03
MACHINE LEARNING · PEOPLE ANALYTICS
Employee Attrition Prediction
An interpretable classification workflow focused on identifying employees at higher attrition risk.
03 / CASE STUDIES
The reasoning behind
the work.
Problems, architecture, methodology, trade-offs and evidence behind selected work.
CASE STUDY / 01
DATA ENGINEERING · ECONOMIC INTELLIGENCE
Steel Indicator
Building an auditable economic indicator from fragmented public data.
- PROBLEM
- Fragmented public sources and changing policy parameters.
- ENGINEERING
- Immutable vintages and source provenance.
- METHODOLOGY
- Versioned index methodology and declared proxies.
- RELIABILITY
- 529 automated tests.
CASE STUDY / 02
APPLIED RESEARCH · DATA SCIENCE
Developer Market Research
Research and data analysis developed during my time at Rocketseat, with findings on women's representation in technology reaching CNN Brasil.
- QUESTION
- What does the Brazilian technology workforce look like?
- RESEARCH
- Market and workforce data analysis, conducted during my time at Rocketseat.
- FINDING
- Women represented a minority of technology employment in the reported analysis.
- IMPACT
- The finding reached CNN Brasil coverage.
04 / EXPERIENCE
Where I've worked
and what I've built.
Professional experience across finance, consulting and technology — applying analytics, machine learning, experimentation and data products to real business problems.
Resume↗2025 — 2026
Banco BV
People Analytics Analyst Pleno · Data Analytics
Built and evolved analytics, forecasting and decision-support products covering a workforce of 4,000+ employees and serving multiple levels of leadership. Worked across SQL Server, Power BI, Python and Databricks.
SQL Server · Power BI · Python · Databricks
2024 — 2025
BIP Consulting
People Analytics · Data Analytics
Took ownership of People Analytics operations and redesigned monthly international reporting, reducing consolidation from about one week to one day. Built ETL and automation flows with Power Automate, Python and Power Query.
Python · Power Query · Power Automate · ETL
2022 — 2023
Contmatic Phoenix
Data Science Junior · Growth & Marketing Analytics
Worked across experimentation, segmentation, churn/LTV, funnels and campaign analytics on a base of ~1M leads and ~60k users. A series of data-driven optimizations contributed to ~11% higher conversion and ~20% lower CAC.
Python · SQL · Experimentation · Growth Analytics
2021 — 2022
Rocketseat
Data Science Junior · Growth & Customer Analytics
Applied data science to segmentation, retention, cohorts and growth analytics across 60k+ paying students. A decision-tree segmentation initiative contributed to ~15% higher course-purchase conversion.
Python · R · SQL · Customer Analytics
05 / RESEARCH & RECOGNITION
Research and milestones
that shaped my work.
Academic investigations and early projects across statistics, forecasting and applied data science.
RESEARCH / 01
Wavelet Multivariate Time Series Analysis
UFSCar · Undergraduate Thesis · 2023
Undergraduate statistics research examining how relationships among financial markets change across time and scale using wavelet methods.
Time Series · Statistics · Wavelets
View research↗RECOGNITION / 01
FarmIA — Santander Data Challenge
1st Place · 2020
First-place data challenge project developed by a five-person team, using statistical modeling and agrometeorological data to support agricultural planning.
1ST PLACE · 100+ TEAMS
Applied Data Science · Agriculture
GitHub↗RESEARCH / 02
Retail Sales Forecasting
Digital House · Final Data Science Project
Academic forecasting project exploring monthly store-level sales with SARIMAX, chronological validation and a historical Flask prototype.
ACADEMIC PROJECT
Forecasting · SARIMAX · Time Series
GitHub↗
06 / CAPABILITIES
Tools and methods I use to
turn ideas into working systems.
01 / APPLIED AI
- LLM Applications
- AI-assisted Workflows
- Structured Outputs
- Prompt & Context Engineering
- AI Automation
02 / MACHINE LEARNING
- Regression
- Classification
- Gradient Boosting
- Forecasting
- Survival Analysis
- Experimentation
- Model Evaluation
03 / DATA
- Python
- SQL
- Pandas
- Power BI
- Data Modeling
- Data Pipelines
- Data Quality
04 / ENGINEERING
- Git & GitHub
- Docker
- Testing
- MLflow
- APIs
- Streamlit
- Automation
07 / CONTACT